Andrew Slimmon

Background

Andrew Slimmon is a Managing Director at Morgan Stanley Investment Management where he is the lead Senior Portfolio Manager on all long equity strategies for Applied Equity Advisors. Andrew is also a member of the Morgan Stanley Wealth Management Global Investment Committee. He has 32 years of investment management experience. He began his career at Morgan Stanley in 1991 as an Advisor in Private Wealth Management, and later served as the Chief Investment Officer of the Morgan Stanley Trust Company. Prior to joining the firm, Andrew was a buy-side equity research analyst with ARCO Investment Management. He began his investment career as an analyst and then portfolio manager for Brown Brothers Harriman, a private bank. He is a regular guest on CNBC. Additionally, he has appeared on CNBC Europe and Bloomberg TV and is quoted regularly in The Wall Street Journal, Barron’s, Bloomberg, and Reuters. Andrew received a B.A. in economics from the University of Pennsylvania and an MBA from the University of Chicago.

Strategies

By employing quantitative models, the team aims to identify 200-300 stocks that, in aggregate, have exposure to factors it believes will drive returns in the current market environment. The final portfolio is designed to have a modest tracking error and align closely with the Russell 1000 Index in terms of industry, sector, style and company size.

Using a combination of quantitative models and stock-specific research, the strategy aims to invest in approximately 15 - 20 global companies with attractive valuations and above-average appreciation potential.

Using a combination of quantitative models and stock-specific research, the strategy aims to invest in approximately 30-60 global companies with attractive valuations and above-average appreciation potential.

Using a combination of quantitative models and stock-specific research, the strategy aims to invest in approximately 30-60 U.S. companies with attractive valuations, above-average appreciation potential and competitive dividend yields.

By employing quantitative models, the team aims to identify 200-300 stocks that, in aggregate, have exposure to factors it believes will drive returns in the current market environment. The final portfolio is designed to have a modest tracking error and align closely with the Russell 1000 Index in terms of industry, sector, style and company size.

Using a combination of quantitative models and stock-specific research, the strategy aims to invest in approximately 15 - 20 global companies with attractive valuations and above-average appreciation potential.

Using a combination of quantitative models and stock-specific research, the strategy aims to invest in approximately 30-60 global companies with attractive valuations and above-average appreciation potential.

Using a combination of quantitative models and stock-specific research, the strategy aims to invest in approximately 30-60 U.S. companies with attractive valuations, above-average appreciation potential and competitive dividend yields.

The information on this page is for informational purposes only. It is intended for the benefit of third party issuers and those seeking information about alternatives investment strategies. The information contained herein does not constitute and should not be construed as an offering of advisory services or an offer to sell or a solicitation of an offer to buy any securities in any jurisdiction in which such offer or solicitation, purchase or sale would be unlawful under the securities, insurance or other laws of such jurisdiction.

All investing involves risks, including a loss of principal. Alternative investments are speculative and involve a high degree of risk. These investments are designed for investors who understand and are willing to accept these risks. Performance may be volatile, and an investor could lose all or a substantial portion of his or her investment.

Please refer to the strategy detail page for important information on the strategy, including additional risk considerations.

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